AI ML Architect

Valuelabs; Hyderabad; Hybrid; INR 4,500,000 - 7,500,000; Full time

Job summary

Valuelabs is seeking an experienced AI/ML leader to drive architecture and delivery of production-grade AI systems in cloud environments. The role requires 10+ years in AI/ML with at least 4 years in leadership, and hands-on expertise in Python, ML tooling, and MLOps.

You will collaborate with global clients across BFS, healthcare, and enterprise software. The ideal candidate will guide ML strategy, ensure scalable pipelines, and advance GenAI capabilities including fine-tuning and evaluation

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI, ML, or related field.
• 10+ years of experience in AI/ML with at least 4 years in a leadership role.
• Proven experience building and deploying production-grade AI/ML systems in cloud environments (AWS, Azure).
• Deep expertise in Python, SQL, REST APIs, Git, Docker, Kubernetes.
• Experience with ML techniques including supervised/unsupervised, deep learning, NLP, computer vision.
• Experience with LLMs & GenAI: fine-tuning, prompt engineering, RAG, evaluation frameworks.
• Experience working with global clients in BFS, Healthcare, Insurance, Publishing, or Enterprise Software.

Responsibilities

• Lead AI/ML initiatives and architecture for scalable, production-grade systems.
• Drive deployment of AI/ML solutions in cloud environments (AWS, Azure).
• Oversee data pipelines, model training, and MLOps practices.

Skills

AI leadership

Python

SQL

REST APIs

Git

Docker

Kubernetes

ML

NLP

Computer Vision

Education

Bachelor's or Master's in CS/DS/AI/ML

Tools

MLflow

Kubeflow

SageMaker

Databricks

CI/CD

Prometheus

Datadog

Job description

Role & responsibilities

Bachelors or Master’s degree in Computer Science, Data Science, AI, Machine Learning, or related field.

• 10+ years of experience in AI/ML, with at least 4 years in a leadership role (e.g., AI/ML Lead, Principal Data Scientist, ML Architect).
• Proven experience building and deploying production-grade AI/ML systems in cloud environments (AWS, Azure).
• Deep expertise in:
• Python, SQL, REST APIs, Git, Docker, Kubernetes
• Machine Learning (Supervised/Unsupervised, Deep Learning, NLP, Computer Vision)
• MLOps tools: MLflow, Kubeflow, SageMaker, Databricks, CI/CD, monitoring (Prometheus, Datadog)
• LLMs & GenAI: Fine-tuning, prompt engineering, RAG, evaluation frameworks
• Experience working with global clients in BFS, Healthcare, Insurance, Publishing, or Enterprise Software.